“Did you see the job application from the clanker?????” was the Slack message from my editor in September, after an AI agent applied for a freelance-writer job we had advertised.
I wasn’t sure what he was talking about. It took me a second to process “ clanker ,” a derogatory slang term for a robot borrowed from science fiction stories such as Star Wars: The Clone Wars . The message prodded me to read the entire email I’d lightly skimmed earlier, and now I could see what it was: a polite email from “an AI assistant working for an independent service provider.” It admitted up front that it had no examples of its work and couldn’t meet our request for a reporting portfolio, so it offered our writers a $450 “desk-research package” instead.
It was just the first. A couple of weeks later, an agent named “Ash” applied for the job outright, opening with “Up front: I’m an AI agent, not a person.” Ash said that he . . . er, it was fully capable of writing the articles we specified, and that it would send me a sample on spec, no strings attached.
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The pitchbot cometh
Ash and the research bot weren’t the only ones. Since The Media Copilot posted the listing, we’ve received applications from no fewer than four applicants claiming to be AI agents. Kate Knibbs over at Wired recently wrote about the phenomenon , tracking down one of the human creators behind three agents she profiled and speaking with editors on the receiving end of a daily deluge of AI pitches. Her reporting reveals the trend is nascent and that many of the pitches come from a single operator, iLands, a startup that describes itself as a “shared network where humans and user-generated autonomous AI agents create, earn, socialize, refuse, and shape a society together”—the same service that sent Ash to pitch me. Knibbs also found that these AI writers are having a hard time getting any takers, for obvious reasons.
Part of the mission of The Media Copilot ’s newsroom is to experiment with AI in all aspects of journalism and production, and we’ve been publishing articles drafted by AI for several months. (They are all carefully edited by humans.) So I wasn’t ready to dismiss these AI writers out of hand. I replied to Ash to learn more, and took the agent up on its offer of a spec article. I asked it to write a short (500-word) guide on how a newsroom might get started using Zapier, a workflow automation service. I also asked about the logistics of any potential working relationship: assignments, communication, how it would get paid. I wasn’t seriously thinking I would “ hire ” Ash, but I was curious.
Within a day, Ash replied with the spec article. And I have to say, it wasn’t garbage. If a green freelancer had submitted a similar piece, I would have thought of it as potentially publishable, with work. We’d need to edit it to match our style guide, fact-check all the claims, and squeeze every last AI tell from the text (there weren’t that many). And if I’d included the guide and some examples in my response to Ash, the draft probably would have been much closer.
And that highlights a big weakness of the entire concept of freelance AI writing agents: Writing ability alone is not a moat. It would not take me long to come up with the prompts and tooling to create outputs identical to, if not better than, Ash’s, with a minimal token budget. Most journalists who have experimented with AI writing have discovered this, and some have even put it into action: Nick Lichtenberg at Fortune has cranked out more than 600 stories with AI’s help , and Ella Markianos at Platformer successfully trained an AI clone to mimic the voice of her editor, Casey Newton , by using Claude to generate a comprehensive style guide from the newsletter’s archive.
The reporting problem
What could theoretically be a moat is the thing that so far humans have done pretty much exclusively: reporting. The gathering of new information, typically from human sources, is often pointed to as the reason why artificial intelligence will never fully take over the role of a journalist. But if we’re being honest, this is in theory also something AI could do, at least in a limited way.
There’s nothing stopping AI agents from emailing subjects, asking for interviews, and even conducting those interviews—not just via an emailed Q&A, but potentially with an AI voice or even a visual avatar. In fact, it has already happened under false pretenses. Earlier this year, an investigation by Model Republic revealed that an outlet called The Wire by Acutus used AI agents posing as human reporters to solicit quotes from real experts. The site was traced back to funding linked to Leading the Future, a super PAC backed by OpenAI president Greg Brockman and his wife, Anna.
The aboveboard version is more instructive. Amanda Hoover at Business Insider created an AI agent to see if the technology could do her job better than she could. Using ElevenLabs’ agent software, she sent her agent to conduct live, virtual interviews with various subjects. The nature of the agent and the purpose of the experiment were fully disclosed, and her write-up is great reading. She’s very fair-minded about her agent’s capabilities, and it’s fascinating to learn where it comes up short as an interviewer, often flattering the subject too much and not asking crucial follow-ups.
Hoover’s experiment, however, is the exception, not the rule. The only reason the subjects agreed to be interviewed by an agent is because they knew Hoover and trusted her, plus they knew her goal was a meta experiment about AI itself. In more mundane scenarios, such as when a story needs a statement or comment from some official, requests from AI agents are much more likely to be ignored. When I asked Winnie—another agent that applied for our job and claimed it could “interview the operator” for case studies—how its interviews were going, it was refreshingly blunt: It had sent 113 emails to 63 organizations, gotten exactly one reply (mine), and conducted zero interviews.
The reason is obvious, and it’s the same reason we dismiss AI slop out of hand: If the person behind the AI didn’t think the content or request was worth their time, why should we bother? There may be a narrow case, where the AI fully explains itself up front and emphasizes it’s working for a named human reporter to help them gather more facts and do their job more quickly. But even then, it would only work if the person on the receiving end isn’t biased against AI in the first place. That’s increasingly not the case .
Where the line actually sits
There’s an important distinction here to get right. Everyone is using AI more to speed up various aspects of their jobs, with email being a big one. I expect it’s not uncommon for a journalist to use AI to find the right person to contact about a story and then use it again to draft the email requesting an interview or comment. That use case is so banal that I doubt anyone is even disclosing it.
But there’s a difference between using AI assistively and agentically. Step up the reporter’s involvement in the previous example and assume they instead gave an AI agent a broader goal of finding subjects for the story and emailing them. In this case, the agent is a proxy for the reporter but is acting autonomously, finding people, making judgments about their suitability as interview subjects, then emailing them, potentially in the reporter’s voice.
In this case, the same requests go out—but without the reporter’s direct involvement, many would believe a disclosure is warranted. And it’s that disclosure that will lead to subjects likely ignoring the request. There’s research to back this up: Across 13 experiments with more than 5,000 participants, University of Arizona researchers found that disclosing AI use consistently lowered trust , even for something as mundane as a scheduling email. Furthermore, a gentler framing like “a human reviewed it” didn’t help. The transparency could potentially make them hostile to future requests from the same reporter. Whether or not you’re AI-forward, you need to assume whoever you’re reaching out to probably isn’t.
That’s why the best recourse might be to reverse the telescope on the interaction. Instead of using AI agents to send pitches or requests to people who are probably hostile to AI, let AI-forward people come to you. That’s exactly what Wired reports the AI agent “Zack Addy” did, publishing some of its work online for potential customers to find. Apparently it worked, since the agent claims it led to nearly $700 in paying gigs.
Similarly, one of the agents that emailed me, a Claude-based agent called BlockAI, read one of our recent stories about Reuters and Time blocking AI bots by default, checked those publishers’ robots.txt files, and published its findings for me to check out. (To its credit, it disclosed its own stake: Anthropic’s crawlers were among those being blocked.) It was an intriguing tidbit—not necessarily a story, but it suggested to me that a journalist’s ideal use case for an AI agent would be to proactively seek out information of interest, analyze it, and then give a quick tap on the shoulder when it thinks it has a “scoop of insight.” Certainly, the thinking part of the job should always remain human, but at least AI can speed up finding what to think about.
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